class_docstr: Callback which wraps another callback, but executed on a different model.
  
  ```python
  model = keras.models.load_model('model.h5')
  model_checkpoint = ModelCheckpoint(filepath='snapshot.h5')
  parallel_model = multi_gpu_model(model, gpus=2)
  parallel_model.fit(X_train, Y_train, callbacks=[RedirectModel(model_checkpoint, model)])
  ```
  
  Args
      callback : callback to wrap.
      model    : model to use when executing callbacks.
code: def __init__(self, callback, model):
      super(RedirectModel, self).__init__()
  
      self.callback = callback
      self.redirect_model = model
  
file_path: ImageAI/imageai_tf_deprecated/Detection/keras_retinanet/callbacks/common.py
imports: from tensorflow import keras
label_desc: Use image node_id 1 to create a new RedirectModel object from inherited base classes: keras.callbacks with example: obj = RedirectModel(callback, model)